How many people cross the crossing between the Engineering and Science building? 🚶‍♂️

Scatter plot showing pedestrian counts throughout the day by weather type. A smoothed line shows a midday peak in pedestrian activity.

The plot above is a scatter plot with a regression line. It has the following features:

  • Time (24-Hour) of Day plotted on the x-axis
  • Pedestrian counts on the y-axis
  • Points are colour-coded by weather (Pink: Sunny, Purple: Cloudy, Blue: Rainy)
  • Blue-regression line that captures the overall trend in pedestrian activity

Interpratation of Plot:

  • Midday Peak: The count of pedestrians tends to be higher between 11am and 2pm, showing the lunchtime surge that usually occurs.
  • Lower counts early & late: Fewer pedestrians are observed early in the morning and later in the evening.
  • Relationship with weather and pedestrian count: It is very difficult to interpret a relationship with weather and the pedestrian count in this plot.

Is there a relationship with the weather condition and pedestrians crossing? 🌤️

Average number of of pedestrians observed under different weather conditions.
Average number of of pedestrians observed under different weather conditions.

The plot above is a bar graph. It has the following features:

  • Weather type on the x-axis
  • Average numbers of pedestrians on the y-axis
  • Bars that are colour-coded by weather (Pink: Sunny, Purple: Cloudy, Blue: Rainy)

Interpratation of Plot:

  • Sunny Weather has the highest average pedestrian count, suggesting that people are more likely to be out walking when it’s clear and pleasant.
  • Cloudy Weather comes after, with a slightly lower average.
  • Rainy Weather has the lowest average pedestrian activity, which is expected since people may avoid walking in the rain.

How safe are people being?! 🚦

Pie charts of phone use and crossing early
Pie charts of phone use and crossing early

The plots above are a pie charts. They have the following features:

  • Phone Use Chart:
    • Blue = Pedestrians who used their phone while crossing.
    • Pink = Pedestrians who did not use their phone.
  • Early Crossing Chart:
    • Blue = Pedestrians who crossed before the green light.
    • Pink = Pedestrians who waited for the green signal.
  • Uses coord_polar() to create the circular pie representation

Interpratation of Plots:

  • A majority of pedestrians did not use their phone while crossing, which suggest good practice for road crossing safety.
  • A good chunk of pedestrian observations still use their phone suggesting a potential distraction issue, which may raise safety concerns for road users
  • The early crossing chart shows that most pedestrians crossed before the green light, reflecting potential impatience, urgency, or reduced perception of risk.

Does the time of day have anything to do with this? ⏰

Grouped bar graph of observations by hour and phone use
Grouped bar graph of observations by hour and phone use

The plot above is a grouped bar chart. It has the following features:

  • X-axis shows hour of day
  • Y-axis shows number of pedestrian observations
  • Bars are colored by phone use: pink = used phone, blue = did not use phone
  • Bars grouped by hour to compare phone vs. no-phone behavior over time

Interpretation:

  • Phone use is generally less frequent than non-use
  • non-usage peaks are seen around 8 AM, 2 PM, and 6 PM, possibly related to commuting or lunch times
Grouped bar graph of observations by hour and early crossing
Grouped bar graph of observations by hour and early crossing

The plot above is a grouped bar chart. It has the following features:

  • X-axis = Hour of day
  • Y-axis = Number of observations
  • Bars grouped by early crossing vs waiting
  • Pink = crossed before green, blue = waited

Interpretation:

  • In most hours, not waiting is more common, suggesting that people may generally be in a rush at these times
  • Between 2 PM and 5 PM, early crossings increase significantly
  • This may reflect impatience or lower perceived traffic risk at those times